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Introduction to R for Business Intelligence

You're reading from  Introduction to R for Business Intelligence

Product type Book
Published in Aug 2016
Publisher Packt
ISBN-13 9781785280252
Pages 228 pages
Edition 1st Edition
Languages
Author (1):
Jay Gendron Jay Gendron
Profile icon Jay Gendron
Toc

Table of Contents (19) Chapters close

Introduction to R for Business Intelligence
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface
1. Extract, Transform, and Load 2. Data Cleaning 3. Exploratory Data Analysis 4. Linear Regression for Business 5. Data Mining with Cluster Analysis 6. Time Series Analysis 7. Visualizing the Datas Story 8. Web Dashboards with Shiny References
Other Helpful R Functions R Packages Used in the Book
R Code for Supporting Market Segment Business Case Calculations

Converting inputs to data types suitable for analysis


Another aspect of data cleaning is investigating the input data and shaping it to conform to your analysis design needs. The third step of the SFCA approach is convert. Specifically, converting the data from one data type to another.

Converting between data types

The R environment stores data in one of the several data types. You will experience five different data types in the Bike Sharing Analysis Project:

Data type

Explanation

Example

Numeric

A number having a decimal value

9.84

Integer

A number without decimals

3

Character

A string variable

"www.google.com"

Factor

A categorical variable that has a character and integer representation

"ad campaign", "blog": 1,2

Date

A date or time in various formats

2016-02-16 18:56:57 EST

Each data type has different properties consistent with definitions used in disciplines such as computer science, mathematics, and statistics. Some R library packages require input...

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